Data Science Office
May 12, 2022
Hadi Shafiee, PhD | Brigham and Women's Hospital
The advancements in nanotechnologies, computer programming particularly machine learning, and consumer electronics such as smartphones have allowed the development of accurate, affordable mobile health diagnostics for disease detection, treatment monitoring, or treatment planning at the point-of-care. In this talk, Dr. Shafiee will showcase some of the work done by his team on the development of AI-engineered smartphone-enabled devices and software to address unmet clinical needs particularly in infectious diseases and infertility management including: (i) AI-enabled, smartphone-based nanoparticle optical systems for point-of-care viral diagnostics; (ii) smartphone-enabled bioassays for male infertility screening through deep learning-based sperm image analysis; (iii) smartphone-enabled salivary bioassay for ovulation prediction through deep learning-based saliva ferning image processing; (iv) embryo assessment and selection using deep learning; and (v) adaptive adversarial neural networks for the analysis of lossy and domain-shifted medical image datasets.